Defect Diagnostics of Rolling Element Bearing Using Fuzzy Dichotomy Technique

Abstract

The monitoring and diagnostics of the bearing have been received considerable attention for many years because the majority of problems in rotating machines are caused by faulty bearings. The malfunction of rotating machinery in plants due to some defects may cause shutdown of the plants, resulting in high maintenance cost. Overly generalized predictions are problematic due to concept classification. In particular, the boundaries among classes are not always clearly defined. To avoid such problems, the idea of fuzzy classification was proposed. In this paper, in order to automatize the diagnosis of a rolling element bearing using the fuzzy classification along with their construction algorithm, the fuzzy dichotomy techique as an acquisition of structured knowledge from held case history data is used for validating the diagnosis capability.